Defining discovery:is Google Scholar a discovery platform? An essay on the need for a new approach to scholarly discovery

This essay discusses the concept of discovery, intended as content discovery, and defines it in the new context of Open Science, with a focus on Social Sciences and Humanities (SSH). Starting from the example of Google Scholar, the authors show that this well established service does not address the current needs, practices, and variety of discovery. Alternatives in terms of technical choices, features, and governance, do however exist, offering richer and more open discovery. The paper presents in particular the implementations and research work of the H2020 project TRIPLE (Transforming Research through Innovative Practices for Linked Interdisciplinary Exploration). Dedicated to the building of a discovery platform for the SSH, the project is meant to address the specificities and evolution of discovery in this field. Prevailing scholarly resource platforms like Google Scholar limit discovery by focussing only on publications, and favouring through their algorithm well-cited papers, English content, and discipline-specific resources. A limitation in the context of cross-disciplinary and collaborative Open Science, such a service more specifically hinders discovery in the SSH. Characterized by a fragmented landscape, a variety of languages, data types, and outputs, research in the SSH requires services that fully exploit discovery potentialities. Moreover, a survey conducted within the TRIPLE project showed that most SSH researchers use Google Scholar as their starting point, and that they recognise the lack of control they have with this system. Beyond the extension of features and content, transparency is the other important criterion for the building of an Open Infrastructure actually serving the research community. In light of this, we present in some detail the GoTriple platform, which exploits today's technological potential and incorporates the best known functionalities in order to unveil more and innovative scholarly outputs and lead to international and interdisciplinary research project collaborations

agINFRA - where agriculture, biodiversity and information technology meet

This poster will provide a brief introduction to and overview of the agINFRA project, a research infrastructure project funded by the EU. The project is developing a data infrastructure to support agricultural scientific communities through promoting data sharing and the development of trust in agricultural sciences. Members of the project are working to provide tools, hosted in a scientific gateway, for creating a linked open data environment for agricultural scientists. The project will try to remove existing obstacles concerning open access to scientific information (including discovery and use of the data) in agriculture. The project consortium also seeks to improve the preparedness of the agricultural scientific community to face, manage and exploit the abundance of relevant data that is (or will become) available to agricultural researchers as data becomes more openly available. It is intended that the project will promote research on food and agriculture, including research to adapt to, and mitigate climate change, and access to research results and technologies at national, regional and international levels. The overall aim of the project being to improve access to knowledge by creating a high level of interoperability between agricultural and other data resources

Security Aspects in Web of Data Based on Trust Principles. A brief of Literature Review

Within scientific community, there is a certain consensus to define "Big Data" as a global set, through a complex integration that embraces several dimensions from using of research data, Open Data, Linked Data, Social Network Data, etc. These data are scattered in different sources, which suppose a mix that respond to diverse philosophies, great diversity of structures, different denominations, etc. Its management faces great technological and methodological challenges: The discovery and selection of data, its extraction and final processing, preservation, visualization, access possibility, greater or lesser structuring, between other aspects, which allow showing a huge domain of study at the level of analysis and implementation in different knowledge domains. However, given the data availability and its possible opening: What problems do the data opening face? This paper shows a literature review about these security aspects

Security Aspects in Web of Data Based on Trust Principles. A brief of Literature Review

Within scientific community, there is a certain consensus to define "Big Data" as a global set, through a complex integration that embraces several dimensions from using of research data, Open Data, Linked Data, Social Network Data, etc. These data are scattered in different sources, which suppose a mix that respond to diverse philosophies, great diversity of structures, different denominations, etc. Its management faces great technological and methodological challenges: The discovery and selection of data, its extraction and final processing, preservation, visualization, access possibility, greater or lesser structuring, between other aspects, that allow showing a huge domain of study at the level of analysis and implementation in different knowledge domains. However, given the data availability and its possible opening: What problems do the data opening face? This paper shows a literature review about these security aspects

Spatial Discovery and the Research Library: Linking Research Datasets and Documents

Academic libraries have always supported research across disciplines by integrating access to diverse contents and resources. They now have the opportunity to reinvent their role in facilitating interdisciplinary work by offering researchers new ways of sharing, curating, discovering, and linking research data. Spatial data and metadata support this process because location often integrates disciplinary perspectives, enabling researchers to make their own research data more discoverable, to discover data of other researchers, and to integrate data from multiple sources. The Center for Spatial Studies at the University of California, Santa Barbara (UCSB) and the UCSB Library are undertaking joint research to better enable the discovery of research data and publications. The research addresses the question of how to spatially enable data discovery in a setting that allows for mapping and analysis in a GIS while connecting the data to publications about them. It suggests a framework for an integrated data discovery mechanism and shows how publications may be linked to associated data sets exposed either directly or through metadata on Esri’s Open Data platform. The results demonstrate a simple form of linking data to publications through spatially referenced metadata and persistent identifiers. This linking adds value to research products and increases their discoverability across disciplinary boundaries. Current data publishing practices in academia result in datasets that are not easily discovered, hard to integrate across domains, and typically not linked to publications about them. For example, discovering that two datasets, such as archaeological observations and specimen data collections, share a spatial extent in Mesoamerica, is not currently supported, nor is it easy to get from those data sets to relevant publications or other documents. In our previous work, we had developed a basic linked metadata model relating spatially referenced datasets to documents. The research reported here applies the model to a collection of spatially referenced researcher datasets, capturing metadata and encoding them as linked open data. We use existing RDF vocabularies to triplify the metadata, to make them spatially explicit, and to link them thematically. Our latest research has produced a simple and extensible method for exposing metadata of research objects as a library service and for spatially integrating collections across repositories

Analysis of the Usability of Automatically Enriched Cultural Heritage Data

This chapter presents the potential of interoperability and standardised data publication for cultural heritage resources, with a focus on community-driven approaches and web standards for usability. The Linked Open Usable Data (LOUD) design principles, which rely on JSON-LD as lingua franca, serve as the foundation. We begin by exploring the significant advances made by the International Image Interoperability Framework (IIIF) in promoting interoperability for image-based resources. The principles and practices of IIIF have paved the way for Linked Art, which expands the use of linked data by demonstrating how it can easily facilitate the integration and sharing of semantic cultural heritage data across portals and institutions. To provide a practical demonstration of the concepts discussed, the chapter highlights the implementation of LUX, the Yale Collections Discovery platform. LUX serves as a compelling case study for the use of linked data at scale, demonstrating the real-world application of automated enrichment in the cultural heritage domain. Rooted in empirical study, the analysis presented in this chapter delves into the broader context of community practices and semantic interoperability. By examining the collaborative efforts and integration of diverse cultural heritage resources, the research sheds light on the potential benefits and challenges associated with LOUD.Comment: This is the preprint version of a chapter submitted to be included in the book "Decoding Cultural Heritage: a critical dissection and taxonomy of human creativity through digital tools", to be published by Springer Nature. The chapter is currently undergoing peer review for potential inclusion in the boo

a digital humanities platform to explore the Portuguese cultural heritage

LISBOA-01-0145-FEDER-022139The ROSSIO Infrastructure is developing a free and open-access platform for aggregating, organising, and connecting the digital resources in the Social Sciences, Arts and Humanities provided by Portuguese higher education and cultural institutions. This paper presents an overview of the ROSSIO Infrastructure, its main objectives, the institutions involved, and the services offered by the infrastructure’s aims through its platform—namely, a discovery portal, digital exhibitions, collections, and a virtual research environment. These services rely on a metadata-aggregation solution for bringing the digital objects’ metadata from the providing institutions into ROSSIO. The aggregated datasets are converted into linked data and undergo an enrichment process based on controlled vocabularies, which are developed and published by ROSSIO. The paper will describe this process, the applications involved, and how they interoperate. We will further reflect on how these services may enhance the dissemination of science, considering the FAIR principles.publishersversionpublishe

OpenAIREplus

Directions the outcomes of the OpenAIRE project, which implements the EC Open Access (OA) pilot. Capitalizing on the OpenAIRE infrastructure, built for managing FP7 and ERC funded articles, and the associated supporting mechanism of the European Helpdesk System, OpenAIREplus will “develop an open access, participatory infrastructure for scientific information”. It will significantly expand its base of harvested publications to also include all OA publications indexed by the DRIVER infrastructure (more than 270 validated institutional repositories) and any other repository containing “peer-reviewed literature” that complies with certain standards. It will also generically harvest and index the metadata of scientific datasets in selected diverse OA thematic data repositories. It will support the concept of linked publications by deploying novel services for “linking peer- reviewed literature and associated data sets and collections”, from link discovery based on diverse forms of mining (textual, usage, etc.), to storage, visual representation, and on-line exploration. It will offer both user-level services to experts and “non-scientists” alike as well as programming interfaces for “providers of value-added services” to build applications on its content. Deposited articles and data will be openly accessible through an enhanced version of the OpenAIRE portal, together with any available relevant information on associated project funding and usage statistics. OpenAIREplus will retain its European footprint, engaging people and scientific repositories in almost all 27 EU member states and beyond. The technical work will be complemented by a suite of studies and associated research efforts that will partly proceed in collaboration with “different European initiatives” and investigate issues of “intellectual property rights, efficient financing models, and standards”.Acknowledgments. This work was supported in part by Open Access Infrastructure for Research in Europe (OpenAIRE) EU project, the Bulgarian National Science Fund under the Project D002-308 "Automated Metadata Generating for e-Documents Specifications and Standards"

Federated Query Processing

Big data plays a relevant role in promoting both manufacturing and scientific development through industrial digitization and emerging interdisciplinary research. Semantic web technologies have also experienced great progress, and scientific communities and practitioners have contributed to the problem of big data management with ontological models, controlled vocabularies, linked datasets, data models, query languages, as well as tools for transforming big data into knowledge from which decisions can be made. Despite the significant impact of big data and semantic web technologies, we are entering into a new era where domains like genomics are projected to grow very rapidly in the next decade. In this next era, integrating big data demands novel and scalable tools for enabling not only big data ingestion and curation but also efficient large-scale exploration and discovery. Federated query processing techniques provide a solution to scale up to large volumes of data distributed across multiple data sources. Federated query processing techniques resort to source descriptions to identify relevant data sources for a query, as well as to find efficient execution plans that minimize the total execution time of a query and maximize the completeness of the answers. This chapter summarizes the main characteristics of a federated query engine, reviews the current state of the field, and outlines the problems that still remain open and represent grand challenges for the area

Transforming Library Catalogs into Linked Data

Traditionally, in most digital library environments, the discovery of resources takes place mostly through the harvesting and indexing of the metadata content. Such search and retrieval services provide very effective ways for persons to find items of interest but lacks the ability to lead users looking for potential related resources or to make more complex queries. In contrast, modern web information management techniques related to Semantic Web, a new form of the Web, encourages institutions, including libraries, to collect, link and share their data across the web in order to ease its processing by machines and humans offering better queries and results increasing the visibility and interoperability of the data. Linked Data technologies enable connecting related data across the Web using the principles and recommendations set out by Tim Berners-Lee in 2006, resulting on the use of URIs (Uniform Resource Identifier) as identifiers for objects, and the use of RDF (Resource Description Framework) for links representation. Today, libraries are giving increasing importance to the Semantic Web in a variety of ways like creating metadata models and publishing Linked Data from authority files, bibliographic catalogs, digital projects information or crowdsourced information from another projects like Wikipedia. This paper reports a process for publishing library metadata on the Web using Linked Data technologies. The proposed process was applied for extracting metadata from a university library, representing them in RDF format and publishing them using a Sparql endpoint (an interface to a knowledge database). The library metadata from a subject were linked to external sources such us another libraries and then related to the bibliography from syllabus of the courses in order to discover missing subjects and new or out of date bibliography. In this process, the use of open standards facilitates the exploitation of knowledge from libraries.This research has been partially supported by the Prometeo project by SENESCYT, Ecuadorian Government, by CEDIA (Consorcio Ecuatoriano para el Desarrollo de Internet Avanzado) supporting the project: “Platform for publishing library bibliographic resources using Linked Data technologies” and by the project GEODAS-BI (TIN2012-37493-C03-03) supported by the Ministry of Economy and Competitiveness of Spain (MINECO)